Electronica Azi International no. 2 - 2024

Cornel Pazara Contributing Editor

In the ever-evolving landscape of technology, the convergence of Artificial Intelligence (AI) and edge computing has emerged as a transformative force, revolutionizing the way devices process and analyze data in real-time. At Embedded World 2024 in Nuremberg, Germany, this intersection of AI at the edge takes center stage, captivating the attention of industry pioneers and enthusiasts alike. A plethora of companies from the likes of digital stallworths such as Nvidia and Intel as well as the major analog semiconductor companies like Analog Devices, Texas Instruments and Microchip are poised to showcase their latest innovations, pushing the boundaries of what's possible with AI-powered edge computing. From established tech giants to agile startups, each participant brings a unique perspective and a diverse array of products tailored to harness the potential of AI at the edge.

Leading the charge is Intel, unveiling their latest generation of AIenabled processors designed specifically for edge devices. With enhanced performance and power efficiency, these chips promise to unlock new possibilities for AI applications in areas such as smart cities, autonomous vehicles, and industrial automation.

Not to be outdone, NVIDIA will be presenting their state-of-theart GPUs optimized for edge computing, empowering developers to deploy complex AI models directly onto edge devices. This enables real-time decision-making and analysis without relying on cloud connectivity, addressing latency concerns and privacy considerations.

Meanwhile, startups like Edge AI Solutions and SensiML showcase their innovative software platforms, democratizing access to AI development tools for edge devices. Leveraging machine learning algorithms and intuitive interfaces, these platforms empower developers to create custom AI applications tailored to their specific use cases, from predictive maintenance to personalized healthcare.

The Keynote speakers will be AMD’s Salil Raje, Senior Vice President and General Manager, Adaptive and Embedded Computing Group. The other Keynote speaker will be Analog Device’s Fiona Treacy who is Managing Director within the Industrial Automation Business Unit. She will discuss how the Intelligent Edge May Help Enable the Sustainable Factory of the Future.

In addition to hardware and software solutions, Embedded World also features insightful presentations and panel discussions exploring the implications of AI at the edge across various industries. Experts will delve into topics such as edge security, data privacy, and regulatory compliance, providing attendees with a comprehensive understanding of the opportunities and challenges associated with this paradigm shift.

As the curtains rise on Embedded World 2024, the stage is set for a captivating journey into the realm of AI at the edge. With companies at the forefront of innovation, attendees can expect to witness groundbreaking technologies that promise to reshape industries and redefine the future of embedded systems.

DigiKey Hosts Great Board Giveaway, Technical Demos and More at Embedded World 2024

DigiKey, a leading global commerce distributor offering the largest selection of technical components and automation products in stock for immediate shipment, will bring its refreshed brand and Great Board Giveaway to embedded world 2024, April 9-11 in Nuremberg, Germany.

The company will host a wide variety of activities, giveaways and resources during the show at booth 4A-633. Visit the DigiKey booth during the show for the Great Board Giveaway and receive a random draw development board from our supporting partners, including u-blox, NXP Semiconductors, Raspberry Pi and STMicroelectronics At the booth, visitors can also view demos and chat with technical experts at the DigiKey TechBench.

Conference attendees will also have a chance to spin the wheel for free prizes by playing the famous DigiKey slot machines. Plus, the DigiKey Café across from DigiKey’s booth will serve free coffee throughout the conference.

“We look forward to connecting with the embedded community at embedded world 2024,” said Mike Slater, vice president, global business development at DigiKey . “Europe is home to many innovators who are developing the technologies of the future that will advance the burgeoning renewable energy, electric vehicle and IoT markets. At DigiKey, we are energized by enabling that innovation with our supplier partners.”

“DigiKey is proud to be part of the thriving community of embedded experts in Europe and around the globe,” said Ian Wallace, vice president, EMEA at DigiKey. “We are excited to show engineers, designers and buyers at embedded world the many ways we are accelerating their progress with streamlined customer experiences.”

For more information about DigiKey and the giveaways, demos and resources that will be happening at embedded world, visit the DigiKey website.

DigiKey - www.digikey.com

3 | Editorial

3 | DigiKey Hosts Great Board Giveaway, Technical Demos and More at Embedded World 2024

6 | Infineon and Green Hills Software present integrated platform for real-time applications for software-defined vehicles

6 | Microchip Technology Introduces ECC608 TrustMANAGER with Kudelski IoT keySTREAM

7 | NeoCortec to exhibit at Embedded World 2024

8 | Toshiba releases motor control driver IC enhanced with built-in microcontroller and gate driver for efficient and precise motor control

8 | SECO and NXP collaborate to bring Clea, a comprehensive end-to-end AI solution, to industrial and IoT applications

9 | Murata’s multi-band LoRa radio module simplifies wireless design and supply-chain management for IoT device developers

10 | onsemi’s CEM102 Analog Front End, Now Available at Mouser, Provides Low-Current Sensing for Continuous Glucose Monitoring

10 | Microchip Technology Expands Its Serial SRAM Portfolio to Larger Densities and Increased Speeds

11 | Vicor to present modular power conversion solutions for 48V Zonal Architectures at WCX 2024

Transformation for Success

22 | Add Bluetooth 5.3 to Edge IoT Designs Quickly and Cost Effectively

28 | New Powerful Single-Chip RZ/V2H MPU for Next-Gen Robotics with Vision AI și Real-Time Control

30 | Advantages through proximity

32 | Bringing Innovation

Infineon and Green Hills

Software present integrated platform for real-time applications for softwaredefined vehicles

Infineon Technologies AG and Green Hills Software LLC, the global leader in embedded safety and security, have launched an integrated microcontroller-based processing platform for safety-critical real-time automotive systems. The platform combines the safety-certified real-time operating system (RTOS) μ-velOSity™ from Green Hills with Infineon’s new generation of safety controllers AURIX™ TC4x. This provides OEMs and Tier 1 suppliers with a reliable, safe, and secure processing platform to develop domain and zonal controllers as well as drivetrains for electric vehicles for their next-generation software-defined vehicle (SDV) architectures.

Enabling the development of advanced ECUs

New automotive electronic control units (ECU) are essential for the adapted vehicle E/E architecture of SDVs. To develop these ECUs, new microcontrollers are needed that also meet the requirements of safety-critical systems such as zone control, chassis, radar, electric drives, and affordable AI systems, by offering higher performance and advanced features. Infineon addresses this demand with its new family of AURIX TC4x devices that complement its TriCore™ multicore architecture with a safety and security accelerator suite. Moreover, to meet the stringent safety requirements, Green Hills has ported its safety-certified μ-velOSity RTOS to the AURIX TC4x family. The advanced MULTI ® integrated development environment is also supporting this processor family, enabling developers to shorten development times by increasing developer productivity while generating the fastest and smallest code for the AURIX TC4x.

Infineon’s AURIX TC4x family provides an upward migration path from the previous AURIX TC3x family of ASIL-compliant automotive MCUs. AURIX TC4x uses the next-generation TriCore 1.8 and a scalable accelerator suite, including the new Parallel Processing Unit (PPU) as well as several intelligent accelerators, in areas such as data routing, digital signal processing, radar processing and cryptographic computing. The AURIX TC4x family supports high-speed interfaces, including Gigabit Ethernet, PCIe, CAN-XL or 10BASE T1S Ethernet, to provide sufficient communication bandwidth for the next generation of automotive systems.

■ Infineon Technologies | www.infineon.com

Microchip Technology Introduces ECC608 TrustMANAGER with Kudelski IoT keySTREAM

As the world comes to rely on interconnected IoT systems –for everything from household items like smart thermostats, virtual assistant technology and digital door locks to medical and industrial applications – the need for reliable cybersecurity on embedded systems has never been greater. To increase security on IoT products and facilitate easier setup and management, Microchip Technology has added the ECC608 TrustMANAGER with Kudelski IoT keySTREAM, Software as a Service (SaaS) to its Trust Platform portfolio of devices, services and tools.

With security credentials managed and updated in the field via keySTREAM – instead of being limited to a static certificate chain implemented during manufacturing – the ECC608 TrustMANAGER allows custom cryptographic credentials to be accurately provisioned at the end point without requiring supply chain customization and can be managed by the end user. keySTREAM offers a device-to-cloud solution for securing key assets end-to-end in an IoT ecosystem throughout a product’s lifecycle.

Cloud-based software as a service leverages secure authentication ICs to enable self-service custom PKI, streamlined in-field provisioning and lifecycle management for IoT devices

The ECC608 TrustMANAGER relies on a secure authentication IC that is designed to store and protect cryptographic keys and certificates, which are then managed by the keySTREAM SaaS. The combined silicon component and key management SaaS allow the user to set up a self-serve root Certificate Authority (root CA), and the associated public key infrastructure (PKI) secured by Kudelski IoT, to create and manage a dynamic certificate chain and provision devices in the field the first time they are connected. Once claimed in the SaaS account, the devices are automatically activated in the user’s keySTREAM service via in-field provisioning.

Security standards and upcoming regulations are increasingly requiring upgradability of security infrastructure for IoT devices. This is a difficult task with traditionally static IoT security implementations, which require physical upgrades like changing out the security ICs in each device to stay in compliance. With the ECC608 TrustMANAGER, the process is automated and highly scalable, allowing devices to be managed securely and efficiently throughout their lifecycle. It also enables easy device ownership management without needing to change hardware, as security keys are updated digitally from the cloud into the device. This approach streamlines the supply chain processes for distribution partners as well.

This type of dynamic in-field provisioning and device management meets IoT security standards and will be useful in device certificate updates needed to stay in compliance with evolving security requirements. The keySTREAM SaaS allows for ongoing updates of keys designed to prevent and protect against evolving threats and security requirements. In-field provisioning also removes the need for customization for more efficient manufacturing.

■ Microchip Technology | www.microchip.com

NeoCortec to exhibit at Embedded World 2024

Experience how ultra-low power, scalable, easyto-install NeoMesh wireless mesh network technology works and how to create full sensor to cloud solutions

NeoCortec , the experts on wireless connectivity and providers of ultra-low-power bi-directional wireless mesh network hardware and software solutions, will exhibit at Embedded World 2024 in Nuremberg, from 9th April to 11th April 2024 in Hall 3 on stand 526.

Visitors to NeoCortec’s stand can learn more about the features of NeoCortec’s ultralow power, easy-to-install NeoMesh wireless mesh network technology (e.g. very high reliability and scalability) and how it works.

A new demo on the stand and in two of the exhibition halls will showcase how easy it is to create full sensor to cloud solutions using NeoMesh Click boards from MikroE and the IoTConnect cloud solution from Avnet.

Comments Halkier: “We are very much looking forward at attending this year’s Embedded World. It has always been a very interesting and exciting exhibition for us and we are ready to explain and demonstrate our NeoMesh solution to all visitors to our stand and show them how it can work for their respective application.”

■ NeoCortec | https://neocortec.com

Toshiba releases motor control driver IC enhanced with built-in microcontroller and gate driver for efficient and precise motor control

Toshiba Electronics Europe GmbH (“Toshiba”) has launched a motor control driver IC that implements a gate driver and a CPU core together with a comprehensive set of features and capabilities for driving three-phase brushless DC (BLDC) motors and permanent magnet synchronous motors (PMSM) more efficiently. With a focus on performance, flexibility and ease of integration, the TB9M003FG is the first device in Toshiba’s Smart Motor Control Driver (SmartMCD™) family. Typical applications include electric pumps, fans, body control, and thermal management systems in automotive.

The SmartMCD TB9M003FG uses Toshiba’s advanced mixedsignal process technology, combining an Arm® Cortex®-M0 CPU with a vector engine co-processor and pre-drivers to control external B6 N-channel MOSFETs. This level of integration of the device, which is housed in an HTQFP48 thermal enhanced package measuring 9.0mm × 9.0mm, allows for smaller, simpler and lower-cost 30 – 1000W BLDC motor systems. The device simply connects directly to the battery and local interconnect network (LIN) bus, which features a built-in wake-up for power-efficient operation and communication.

The implemented vector engine co-processor enables precise field-oriented control, which is essential for efficient motor control, particularly in applications requiring accurate positioning, torque or speed control. It accelerates the necessary mathematical operations and reduces the load on the CPU. The highspeed PWM frequency and advanced control algorithms contribute to smooth and quiet operation, reducing vibration and noise. Features such as 1-shunt sensorless measurement, reduced component count, and smaller program code size contribute to lower overall system costs.

The operating temperature range (Ta) of the AEC-Q100 (Grade 0) qualified device is -40°C to +150°C, ensuring reliability in harsh automotive environments. The SmartMCD incorporates current limiter, overcurrent, VBAT overvoltage, and overtemperature protection circuitry, and fault detection for undervoltage, external power MOSFET open/short failure and overheating. This eliminates the need for several external circuits, further reducing system cost and saving space and design effort.

■ Toshiba | https://toshiba.semicon-storage.com

SECO and NXP collaborate to bring Clea, a comprehensive end-to-end AI solution, to industrial and IoT applications

SECO S.p.A. is pleased to announce it is working with NXP® Semiconductors (“NXP”), to bring SECO’s Clea software solution to industrial and IoT applications. Clea is the full-fledged AI as a Service (AIaaS) Platform and optimization of Clea on NXP hardware will facilitate the deployment of AI models for device manufacturers across industrial and IoT applications.

SECO, as an NXP Gold Partner and active participant in multiple early-access programs, has demonstrated its proficiency in harnessing NXP’s cutting-edge hardware technologies. This collaboration falls within the framework of the longstanding partnership spanning over 15 years and represents a significant step toward bringing the added value of SECO’s software solutions to the forefront of industrial and IoT applications. This collaboration between SECO and NXP aims to simplify complexity for customers with a ready-made development environment for AI-powered devices across industrial and IoT applications and encompasses multiple technical initiatives.

Clea will natively support NXP’s MCX portfolio on Zephyr, an open-source, real-time operating system. to provide NXP’s customers with a ready-to-use stack to implement industrial and IoT applications. Additionally, i.MX portfolio users will have access to a native integration of Clea on NXP’s Yocto/Debian releases. SECO and NXP intend to roll out a series of reference implementations, documentation, and code samples to empower their respective users to get started with Clea on NXP hardware as quickly as possible.

Further, with NXP’s eIQ® machine learning software development environment, Clea users will gain access to a variety of pre-built applications over time, which will facilitate rapid access to Clea’s IoT, field data and device management functionalities, as well as the enablement of advanced AI capabilities, and empower NXP users to more effectively manage and deploy their edge machine learning models at scale.

“Making it easier for our customers to bring complex products to market is at the core of what NXP does. Combining SECO’s Clea platform with our eIQ machine learning development environment, as well as delivering seamless support for our broad portfolio of MCX MCUs and i.MX applications processors will make it easier for NXP’s customers to bring products to market faster and more easily”, stated Luca Bartolomeo, Senior Director, Industrial Business Development at NXP Semiconductors

“Clea is perfectly positioned to become an Open Standard for data-intensive IoT applications. Being acknowledged for its value by one of the world’s leading technology players marks a strategic milestone and represents yet another substantial technical validation for our platform. We will strive to be a key player in enabling Edge AI thanks to frameworks like NXP’s eIQ machine learning development environment, and we look forward to supporting NXP users in building their next big thing”, stated Massimo Mauri, CEO of SECO.

Murata’s multi-band LoRa radio module simplifies wireless design and supply-chain management for IoT device developers

Murata unveiled its groundbreaking Type 2GT module, a multi-band, low-power radio (LoRa) module which marks a significant leap forward in the development of IoT devices requiring versatile wireless connectivity. This highly integrated module stands out by offering a comprehensive solution that caters to the complex demands of global certification standards, facilitating seamless deployment in diverse regions and industries.

The Type 2GT module is 9.98 × 8.70 × 1.74mm and is built on a PCB housed in a metal case and packaged as a land grid array. The module’s technical prowess is highlighted by its use of Semtech’s advanced LR1121 RF transceiver IC, a thermally compensated crystal oscillator (TCXO), a second 32KHz crystal, an RF switch, and an RF matching network. These components ensure maximum frequency accuracy and reliable performance under varying environmental conditions. For enddevice designers, this translates to simpler and small sized pcb designs, reduced time to market, and lower development costs, thanks to the module’s ease of integration and streamlined certification process.

The Type2GT’s support for multiple frequency bands – including sub-GHz bands, the 2.4GHz ISM band, and the 2.1GHz satellite communications S-band – underscores flexibility and scalability, meeting the needs of various IoT applications such as smart agriculture, Industrial and environmental sensing, building and home automation. Other markets which could benefit from the module’s features include asset tracking, utilities metering, remote-controlled toys and drones. Support for the 2.4GHz ISM band enables higher data rates, common channel plan across the globe and also allows designers to avoid the duty-cycle limitations imposed on sub-GHz communications by European standards.

Murata’s Type2GT module is certified to European CE and American FCC standards, the Japanese TELEC standard, and the Canadian IC standard enabling designers to reuse module RF test reports across different certification authorities.

For more information on Murata’s Type2GT module visit https://www.murata.com/en-global/products/connectivitymodule/lpwa/overview/lineup/type-2gt

■ Murata | www.murata.com

onsemi’s CEM102 Analog Front End, Now Available at Mouser, Provides Low-Current Sensing for Continuous Glucose Monitoring

Mouser Electronics, Inc., the industry’s leading New Product Introduction (NPI) distributor with the widest selection of semiconductors and electronic components™, is now stocking the CEM102 analog front end (AFE) from onsemi

The CEM102 sensor accurately measures very low currents for continuous glucose monitoring (CGM) and other sensitive tasks. The CEM102 is an analog front end developed for electrochemical sensor applications using amperometric measurements, including Internet of Things (IoT) sensor devices and wearables.

The onsemi CEM102 analog front end, now available at Mouser, is designed for use with the onsemi RSL15 Bluetooth® 5.2 wireless microcontroller.

The CEM102 AFE features a small form factor and low power consumption, making it an ideal choice for compact devices requiring extended battery life. The CEM102 features a highresolution analog-to-digital converter (ADC), multiple digitalto-analog converters (DAC) for bias setting, and a factorytrimmed system. Together, the CEM102 and RSL15 MCU provide very low system power consumption and a supply voltage range of 1.3V to 3.6V; the system can be powered by a 1.5V silver oxide battery or a 3V coin cell.

The CEM102 supports one, two, three or four electrodes, providing detection for abnormal sensor conditions with host processor wake-up.

To learn more about the CEM102 analog front end, visit https://www.mouser.com/new/onsemi/onsemi-cem102-analog-front-end

■ Mouser Electronics | www.mouser.com

Microchip Technology Expands Its Serial SRAM Portfolio to Larger Densities and Increased Speeds

To address a common customer need for bigger and faster SRAM, Microchip Technology has expanded its Serial SRAM product line to include larger densities of up to 4 Mb and increased Serial Peripheral Interface/Serial Quad I/O™ Interface (SPI/SQI™) speed to 143 MHz. The 2 Mb and 4 Mb devices are designed to provide a lower-cost alternative to traditional parallel SRAM products and include optional battery backup switchover circuitry in the SRAM memory to retain data on power loss.

Unlike parallel RAM, which requires large packages and at least 26–35 microcontroller (MCU) I/Os to interface, the Microchip serial SRAM devices come in a lower-cost, 8-pin package and utilize a high-speed SPI/SQI communication bus that only requires 4−6 MCU I/O pins for easy integration. This reduces the need for a more expensive, high-pin-count MCU and can help minimize the overall board footprint.

Product line offers a lower-cost alternative to parallel SRAM with up to 4 Mb density and 143 MHz SPI/SQI™ communications

Addressing the most common drawback to serial SRAM – that parallel is faster than serial memory – the 2 Mb and 4 Mb serial SRAM devices have increased the bus speed capability to 143 MHz with optional quad SPI (4 bits per clock cycle), which greatly minimizes the speed gap between solutions.

“Serial SRAM is a popular solution for engineers who need more RAM than what is available on board their MCU but are looking to reduce cost and overall board size,” said Jeff Leasure, director of Microchip’s memory products business unit. “Microchip’s 2 Mb and 4 Mb serial SRAM devices are intended to replace expensive parallel SRAM with an easy and cost-effective alternative.”

The small-form-factor, low-power, high-performance serial SRAM devices have unlimited endurance and zero write times, making them excellent options for applications involving continuous data transfer, buffering, data logging, metering and other math- and data-intensive functions. These devices are available from 64 Kbit up to 4 Mb in density and support SPI, SDI and SQI bus modes. Visit Microchip’s Memory Products page to learn about the company’s full portfolio of memory devices.

Pricing and Availability

The 2 Mb and 4 Mb serial SRAM devices are available starting at $1.60 each in 10,000-unit quantities. For additional information and to purchase, contact a Microchip sales representative, authorized worldwide distributor or visit Microchip’s Purchasing and Client Services website, www.microchipdirect.com.

■ Microchip Technology | www.microchip.com

Vicor to present modular power conversion solutions for 48V Zonal Architectures at WCX 2024

As the automotive industry moves toward 48V zonal architectures, power system design engineers are looking for new high voltage power conversion solutions that have leading power density, weight and scalability attributes.

Vicor will be presenting five papers at World Congress Experience 2024 (WCX™) in Detroit on April 16 – 18, detailing its innovative approach to 800V and 48V power conversion using new high-density, scalable power modules with proprietary topologies and innovative packaging.

The Vicor papers are:

• Achieving EM conducted emission compliance for high-voltage conversion with switching frequency above 1.3MHz

Presented by: Nicola Rosano, Sr. Strategic System Engineer, EMEA

• Designing 48V zonal architecture that keeps the high voltage inside the BEV battery pack

Presented by: YK Choi, Sr. Field Application Engineer, Vicor, APAC

Kang YoungJae, Chief Engineer, INFAC

• Eliminating the high-voltage precharge with existing hardware in BEV

Presented by: Patrick Kowalyk Automotive, Principal Field Application Engineer, North America

• Migrating to 48V with high efficiency, power density and efficient system cost

Presented by: Patrick Wadden, Global VP, Automotive Business Unit

• The uncertain future of aftermarket loads in a 48V world

Presented by: David McChesney, Strategic Account Manager, North America

Visit us at WCX 2024 and learn more about the Vicor presentations.

About WCX

The WCX™ World Congress Experience is where the engineering community convenes on mobility’s biggest hurdles from mass deployment of electric vehicles to developmental timelines for autonomous vehicles to understating of global supply chain constraints impacting the automotive industry. World Congress Experience is an event of the Society of Automotive Engineers (SAE).

■ Vicor Corporation | www.vicorpower.com

Machine Learning on the edge

Author: Adil Yacoubi, EMEA Sr. Technical Marketing Engineer Microchip Technology Inc.

TODAY’S NEED FOR AI AND ML

Artificial intelligence (AI) and Machine learning (ML) are used in many applications, in industries as diverse as travel, banking and financial services, manufacturing, food technology, healthcare, logistics, transportation, entertainment and many more.

One of the well-known applications is in autonomous driving, where the car can use machine learning to recognize barriers, pedestrians, and other cars. Other uses include predicting or detecting diseases and inspecting circuit boards.

WHAT ACCELERATES AI DEPLOYMENT?

One of the key factors accelerating AI and ML deployment is the growth in computing power allowing complex mathematics calculations to be executed easily and quickly.

There are also increasing numbers of algorithms helping the creation of models and making data inference easier and quicker. Governments and companies are also investing heavily in this area.

The AI/ML tools that help non data scientists easily understand, create, and deploy models are a crucial element and are today more and more available and accessible.

Although model building will be done on the cloud, on high performance machines, we will often want to do the inference locally. This has several benefits, including added security because we are not communicating to the external world. Acting locally means we are not consuming bandwidth and are not paying extra money to send the data to the cloud and then getting the results back.

Some of the benefits of performing inference at the edge include:

• Real time operation/Immediate response

– Low latency, safety operation

• Reduced Cost

– Efficient use of network bandwidth, less communication

• Reliable operation with intermittent connectivity

• Better customer user experience

– Faster response time

• Privacy and security

– Less data to transmit leads to increased privacy

• Lower power consumption

– No need for fast communication

• Local learning

– Better performance by making each product learn individually

Latency is a good driver to perform inference locally because we are not waiting for the information to be sent and the results to be sent back. The Edge can help users by moving machine learning from high performance machines to high end microcontrollers and high-end microprocessor units.

WHAT IS ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING?

Artificial Intelligence was established in the 1950s. Essentially, AI replaces the programming procedure by developing algorithms based on the data, rather than the legacy method of writing them manually.

Machine Learning is a subset of artificial intelligence, where the machine tries to extract knowledge from the data. We provide the machine with prepared data and then ask it to come up with an algorithm that will help predict the results for new fresh set of data.

ML is based on what we call 'supervised learning'. In this technique, the data is labelled, and the results are based on that labelling - we also build the model based on that labelling.

Another technique is deep learning, which works on more complex algorithms, where the data is not labelled. We will mainly consider supervised learning for the Edge in this article.

The basic element of ML is the neural network, which consist of layers of nodes, each node having a connection to either the inputs or to the next layers. There are several types of neural networks. The more we move from machine learning to deep learning, the more we will see complex networks. Deep learning also incorporates some feedback mechanisms, whereas simple ML models have simple forward actions, moving from the data to the output or result.

The quality of this data will determine how accurate the model is. We need to put it together and make it random, as, if it is too organized, models will not be created correctly, and we can end up with bad algorithms.

The second step is to clean and remove the unwanted data. Any set where some futures are missing should be removed. Any states where the data is not needed or any states which are typically unknown should also be removed.

HOW DO YOU “TRAIN” A MACHINE?

The first step is data collection. As we focus on supervised learning, we collect labelled data, so that patterns can be found correctly.

Data must be then separated into two parts, one for training and the other for testing.

The third step is training the algorithm. This is split it into three steps.

The first step is to choose the machine learning classification algorithm. Several ones are available and are suitable to different types of data. Example of machine learning classification algorithm are:

• Bonsai

• Decision Tree Ensemble

• Boosted Tree Ensemble

• TensorFlow Lite for Microcontrollers

• PME

It is important to choose the right model composition as this determines the output you get after running the ML algorithm on the collected data. This may need some data scientist skills but could also be left to the automatic engine provided by several model creation tools.

The second sub-step is the model training operation, which consists of running several iterations to improve the weights of the different layers and the overall accura-

cy of the model. We then need to evaluate the model, which is done by testing the model with a subset of data. The one we have already kept for future testing and evaluation. This set of data is unknown to the model. We can then compare the model output to the well-known results.

Once we have completed these steps, we can use the model created and validate the results by performing inference on targets.

© Microchip Technology

© Microchip Technology

The idea is to take the model in the field, provide it with some inputs and see whether the results are correct.

MICROCHIP SOFTWARE AND TOOLS

Microchip has partnered with several third-party companies, including Edge Impulse, Motion Gestures and SensiML. We also support popular frameworks such as TensorFlow Lite For Microcontrollers, which is part of Microchip Harmony framework. TensorFlow Lite can be used to create models across all Microchip portfolio, except for 8-bit devices as of today. Microchip microcontrollers and microprocessors are compatible and support TensorFlow Lite. Microchip’s microcontrollers and microprocessor solutions support many applications such as smart embedded vision. They are also a good fit for predictive maintenance based on either vibration, power measurement or on sound monitoring. Microchip portfolio can be used in gesture recognition and, coupled with touch capabilities, can make it easier to control human machine interfaces.

Microchip provides high performance PCI switches which enable the interconnection of GPUs and helps with model training.

Data collection can be done using microcontrollers, microprocessor units, FPGAs, and sensors. All available in Microchip portfolio.

Data validation and inference operation can both be done on microcontrollers, microprocessors, or on FPGAs.

Overall, these solutions make ML easy to implement using the Microchip portfolio. When it comes to software, Microchip machine learning centre contains is a great location where our latest solutions are presented.

In addition of Microchip Harmony framework supporting popular frameworks, machine learning software is provided thanks to several partnerships. One partnership is with Edge Impulse, which has a full TinyML pipeline where we can collect the data, build the model, and deploy it. This partner uses TensorFlow Lite for microcontrollers. One of the biggest advantages here is that Edge Impulse’s code is completely open-source and royalty free.

Another partner is Motion Gestures, which specializes in gesture recognition and can be used to build human machine interfaces. This tool can help create and deploy gestures in minutes, cutting software development time – it also produces satisfactory results for gesture recognitions that approached 100% recognition in out tests.

There are two ways to use this tool, either with touch, the classic way, or motion, using some IMU sensors.

GETTING STARTED

Microchip offers several kits to get developers started in AI and ML. On the microcontrollers side, the SAMD21 ML, SAMD21 Machine Learning evaluation kit with a TDK sensor.

Another variant uses Bosch AMU.

On the motion gesture side, we have a demo with SAMC21 Xplained Pro plus a QTouch touch pad, one of the tools with which you can start to implement your ML gesture recognition application.

The IGaT is a graphic and touch board which also uses ML, with out-of-the-box firmware that has the gesture recognition demo in addition to many other demos for cars, home, entertainment, and others.

Adafruit EdgeBadge - TensorFlow Lite for Microcontrollers is another kit which uses TensorFlow Lite directly.

It has a 2-inch TFT display. EdgeBadge can be used by Arduino community. Several examples are provided such as Sine Wave Demo, Gesture Demo and Micro Speech Demo.

On the high end side, The PolareFire video kit has a dual camera interface, MIPI interface, HDMI interface, and comes with 2GB DDR, 4 SDRAM, a USB2UART interface, and 1GB SPI flash. Out of the box, this kit provides an object detection demo using or based on a ML model.

For more information:

https://www.microchip.com/en-us/education/developer-help/learnsolutions/machine-learning

■ Microchip Technology www.microchip.com

Advantech to showcase industry-leading AIoT solutions at Embedded World

Embedded World, April 9-11 2024, Hall 3, Booth 339

Advantech announced its participation at Embedded World 2024, a trade show taking place in Nuremberg April 9-11, 2024. Visitors will find Advantech’s 160 m2 booth in Hall 3, Booth 339, where the company’s comprehensive portfolio based on different hardware architectures (x86/ARM) and dedicated software services will be on display, fully tailored for different emerging markets such as EV charging and AIintegrated robotics.

A number of live demonstrations – essentially proof-of-concept system demonstrations – will present Advantech’s industryleading scalable industrial Box PCs for end-to-end Edge AI solutions. This includes the AIR-150 system, featuring Advantech’s first integrated HAILO AI acceleration module and based on Intel® 13th Core i5/i3 processors, targeting e.g. AI-based access control applications. Advantech’s AIR-530, a Box solution based on NVIDIA’s IGX platform, will also be on display. It provides 200GbE Ethernet bandwidth and 32 TFLOPS AI computing power, while the compact and high-performance AI Box AIR-030 based on NVIDIA® Jetson AGX Orin™ delivers powerful AI inferencing capabilities. These systems are ideal for energy-efficient autonomous machines and feature versatile I/O options including CANBus for motion control, LAN and optional PoE for camera input, and DI/O for sensor control.

All industrial Box PCs are globally certified, meet industrial standards and come with an industrial roadmap guaranteeing availability for a minimum of 5 to 10 years.

Live AI demonstrations will feature Intel’s new ARC A380E chipset. The integration of the EAI-3101 GPU with Advantech’s Intel-based industrial motherboard AIMB278, which boasts advanced computer vision capabilities, will demonstrate the implementation of AI for age and mood detection. Potential applications include gaming, surveillance, autonomous vehicles and medical, to name a few.

The company will also shine a spotlight on a number of individual high-performance products demonstrating all available board form factors such as Computer-onModules (COMs), Single-Board-Computers (SBCs) and Motherboards. One standout example is the COMe module SOM-5885, which features the latest Intel® 14th Gen Core™ Ultra Processor with up to 14 cores and an integrated ARC GPU.

Two new SBCs, the MIO-5154 and MIO2364, both powered by the latest Intel® Atom® x7000E Series will be presented as well. The 3.5” MIO-5154 caters to various retail applications including self-checkout and smart vending, medical applications like hemodialysis, ventilators and In Vitro Diagnostics (IVD), as well as factory automation tasks encompassing HMI, robotic arms and AGV/AMR systems.

COMPANIES

Meanwhile, the space-saving 2.5” MIO2364 offers an optimal solution for medical automation, HMI interfaces, sensors and gateway deployment, AI boxes and smart camera setups.

Also adding to the SBC-family is the 2.5” RSB-3810, with 8-watt power efficiency that adopts MediaTek’s flagship chipset Genio 1200 and is optimized for IoT applications at the edge, including robotics and industrial IoT.

Advantech will also introduce OSM modules based on Qualcomm and NXP technology, specifically optimized for lowpower applications and for products requiring compliance with 0.8W EU Standby power regulations.

Visitors will also have the opportunity to get close to Advantech’s brand-new Qualcomm SoC board-based portfolio, marking the dawn of a new era of Edge AI applications.

Among the innovations will be the brand-new Flash Memory card SQF 930L in E1.S form factor supporting PCIe GEN4, designed to be hot pluggable and ideal for Hyperscale Solutions

All these versatile building blocks cater to solutions targeting diverse vertical markets including such as EV charging and AI-integrated robotics

Advantech will prominently highlight its rich software and service offerings which strive to meet industrial computing needs comprehensively, with systems like Microsoft Windows IoT and ARM, as well as Ubuntu, along with BIOS modification services, Linux Yocto and QNX support, and BSP maintenance service. Spanning a wide range of functionality from drivers to application software packages, Advantech’s offerings are designed to facilitate the development of complete systems.

Visitors can witness the efficiency of an x86 platform with Slim Bootloader compared to RISC startup times and learn firsthand how Advantech assists in building and maintaining custom Yocto BSP with local engineering support.

A wide range of Industrial Display Solutions and display kits will be presented, readily adjusted to specific applications, with low customization fees and MOQs.

Advantech

www.advantech.com

Make Your Digital Factory a Reality:

DIGITAL TRANSFORMATION FOR SUCCESS

Authors: Tracey Johnson, Senior Marketing Manager

Margaret Naughton, Marketing Engineer Analog Devices

INTRODUCTION

The digital factory, whose operations are built on data, represents a system of component elements working in harmony to optimize operational efficiency across the factory floor. In some ways, it could be likened to the human body. The sensors act as the eyes and ears that allow a central controller – or brain – to be aware of its surroundings. The actuators act as the muscle to make adjustments as required. The factory connectivity network can be equated to the nervous system deployed

Are you interested in how a digital factory works and operates? This article parallels the operation of the digital factory to the workings of the human body, outlining the importance of data as the lifeblood of the digital factory. Explore how digital factory implementations can help realize manufacturing plant operational efficiencies through Intelligent Edge insights.

throughout the body, while the skin is representative of the cybersecurity technology crucial to protecting the data.

BENEFITS OF THE DIGITAL FACTORY

Before exploring the components of the digital factory, let’s first outline the benefits. The benefits of the digital factory are centered on enabling greater productivity, which is transforming the manufacturing landscape. New insights from the digital factory ecosystem help to inform realtime decision-making.

This results in improved product quality and increased overall operational efficiency, culminating in more sustainable production processes. Given that the industrial sector consumes approximately 50% of the world’s total energy1, for manufacturers with a net zero goal, the digital connected factory is at the heart of this transformation. In addition to sustainability benefits, digital factories provide the flexibility and real-time configurability to rapidly respond to evolving changes in consumer demand.

For example, in the healthcare sector, there is an increasing demand for personalized medical devices such as 3D-printed joint implants tailored to an individual patient’s anatomy. As factory designs become more modular and production cells become smaller and more adaptable, workflows can be scheduled and changed in real time, boosting manufacturing speed and supporting the viability of cost-competitive on-shoring efforts across Europe and North America.

SENSORS − THE EYES AND EARS OF THE DIGITAL FACTORY

More sensors and varieties of sensing modalities such as temperature, pressure, flow rate, proximity, and vibration need to be deployed to acquire the necessary data.

Precision measurement and sensing technology is required to continuously sense, measure, and interpret factory assets.

DATA − THE LIFEBLOOD OF THE DIGITAL FACTORY

Both real-time and nonreal-time data, derived from multiple sources across the factory, must be analyzed quickly and reliably, at the Intelligent Edge – where the data is born – and aggregated at a central level to reveal a holistic picture of the complete factory operation.

Operational insights derived from this data are integral to realizing the full operational efficiency potential of the factory.

IO-Link® technology enables sensors to become intelligent.

A pressure sensor locally decides if the pressure exceeds the required threshold and thus only needs to provide the controller with a single Boolean bit variable (yes or no), representing one bit of data instead of a full digital value representing the actual pressure measurement.

Localized decision-making saves communication and processing time, making for efficient distributed control.

ACTUATORS − THE MUSCLE OF THE DIGITAL FACTORY

Actuators, often the unsung heroes of the digital factory, act as the muscle – critical to getting the job done. These actuators are used to control valves, pistons, and other mechanical devices. This allows the flow of fluids to be controlled precisely, ensuring that the correct amount of material is delivered to each part of the process.

Both sensors and actuators need to be tolerant of conditions found in their application space. Harsh factory environments include high temperature and electromagnetic compatibility (EMC) emission exposure, as well as supply voltage transient spikes and mechanical vibration. For these edge sensing and actuating systems, power delivery is another key consideration.

Power delivery performance requirements increase as sensors and actuators become smaller, with the accuracy and quality of the signal acquisition increasing at the same time. This demands highly efficient, low noise power management solutions with reduced footprint, critical in what can often be space constrained designs.

Without the necessary power technology suitable for specific sensing requirements, the real-time configurability benefits of the digital factory cannot be realized.

The anatomy of the digital factory. ©

Figure 1

Benefits of the digital factory. © ADI

Figure 2

EDGE AND CENTRAL INTELLIGENCE − THE BRAIN OF THE DIGITAL FACTORY

Given that the digital factory requires devices at the edge to have increased levels of functionality and intelligence, more computations and analytics must occur within the device itself to enable localized decision-making.

To enable such edge autonomy, local artificial intelligence (AI)/machine learning (ML) engines, low power accelerators, increased memory, and processing power are required. Sensor fusion is another type of edge intelligence where data from multiple different types of sensors can be simultaneously combined to reveal a more accurate measurement – one that would be impossible using sensors singularly.

With new high precision and high bandwidth ADCs, a single sensor front end can be used to monitor multiple sensor elements, saving space and power.

AI microcontroller technology enables neural networks to execute at ultra low power, while low power transmitters enable enhanced diagnostic capabilities even in remote process plants, often an extension of the smart factory.

CONNECTIVITY − THE NERVOUS SYSTEM OF THE DIGITAL FACTORY

Despite this edge device autonomy, for manufacturers to extract valuable and productivity-improving insights from the abundance of available data, the ability to transport, analyze, and merge this data

with existing information streams within the factory is paramount. This requires low latency, time-bound, low power, robust, industrial connectivity technology.

10BASE-T1L is an Ethernet physical layer standard (IEEE 802.3cg-2019) set to dramatically change the process automation industry by significantly improving plant operational efficiency through seamless Ethernet connectivity to field-level devices (sensors and actuators).2

In today’s factories, an information technology (IT) network is deployed at an office/enterprise level. The IT network is traditionally concerned with things like data storage, data analytics, and business applications. While these are important, they are not typically as time critical as data exchange on the factory floor. The network running the production lines on the factory floor is referred to as the operational technology (OT) control network.

Within that control network, there can be multiple different production cells or machines that often have limited ability to communicate with each other. The concept of the converged IT/OT network within the digital factory changes all of this.

It offers one unified factory network, where all devices, machines, and robots are connected and interconnected, and speak the same language. Each IP-addressable device can be communicated with in real time or near real time and be configured independently of other devices on the network.

Key enabling technologies for such a converged digital factory network are Industrial Ethernet, time sensitive networking (TSN), Ethernet-APL (advanced physical layer), and IO-Link. With all devices speaking the same Layer 2 language, it is now possible to control both

Figure

Figure 3 Building blocks of the modern digital factory.

the IT and the OT portions of the network with the same control and network management system, while the time sensitive traffic of the operational network is respected. The sheer volume of both time-critical and nontime-critical traffic demands network upgrades for increased bandwidth to ensure the latency-free delivery of data, which is critical to the high product quality and operational efficiency of the manufacturing plant. The convergence of OT and IT makes scalability opportunities virtually limitless.

CYBERSECURITY − THE LAYER OF SKIN PROTECTING TRUSTED DIGITAL FACTORY DATA

With increased interconnectivity comes the need for heightened data security, as smart factory environments expose people, technology, processes, and intellectual property to cyber threats. This is driving the need for features like secure boot, secure software update, secure transmission authentication, and hardware root of trust. A fundamental aspect of securing a network is the authentication of each new device attempting to connect to the network. It consists of checking that the device is genuine before authorizing any network transaction with it. Like device authentication, secure boot is a must have, ensuring field equipment executes only software coming from a trusted source with public key cryptography employed to verify the digital signature of the firmware.

WHAT TECHNOLOGY SOLUTIONS ARE AVAILABLE TODAY?

Analog Devices has always been valued for innovative precision technology used to sense, measure, and accurately control devices throughout the factory. Combining this with an expansive industrial connectivity and power portfolio, and additional digital capabilities, including AI expertise, ADI has the technology and domain expertise to make advanced digital factory capabilities become a reality.

• Low bandwidth, multichannel sigmadelta ADCs such as the AD4130, family integrate the full analog front-end circuitry for effortless interfacing to multiple sensor types. This enables sensor fusion with advanced diagnostics to support localized fault detection and fast decision-making.

• The industry’s lowest power 10BASE-T1L ADIN1110 MAC-PHY and accompanying ADIN1100 PHY enable the transition to seamlessly connected field devices, bringing Ethernet-APL all the way to the process edge, over 1.7 km of single-pair Ethernet cables.

• For cybersecurity, turnkey, hardwarebased solutions allow customers to easily integrate data security into their products. The DS28S60 and MAXQ1065 are ultra low power secure integrated circuits (ICs) that enable public key cryptography even in the most power and computationalresource constrained designs.

• The MAX78000 AI microcontroller enables neural networks to execute at ultra low power, providing actionable insights from AI at the edge.

THE PATH TO THE PERVASIVE DEPLOYMENT OF THE DIGITAL

FACTORY

Industry surveys suggest that 85% of companies have accelerated digital transformation within their manufacturing plants in the past 2 to 3 years3

However, full digital factory implementations are not the norm yet. The World Economic Forum’s global lighthouse network of leading manufacturers is demonstrating how digitalization strategies and digitally infused operations bring benefits beyond productivity gains to create a base for sustainable, profitable growth. These manufacturers are capitalizing on productivity improvements by unlocking capacity through the deployment of innovative technologies. These technologies accelerate efficiencies and, in turn, yield environmentally favorable outcomes. This is resulting in a dual benefit of increased productivity with increased sustainability – effectively eco-efficiency.

CONCLUSION: MAKE YOUR DIGITAL FACTORY A REALITY

As digital transformation continues to accelerate, factories face both opportunities and challenges. New technologies are key to increased efficiency, but implementing these technologies can be complex and requires thoughtful execution. Leveraging partners with deep domain expertise is paramount to enhancing operations and unlocking these efficiencies. This collaboration lies at the heart of the most robust and adaptable digital factories of tomorrow.

References

1) “Industrial Sector Energy Consumption.” U.S. Energy Information Administration, 2016.

2) Maurice O’Brien and Volker Goller. “Enabling Seamless Ethernet to the Field with 10BASE-T1L Connectivity.” Analog Devices, Inc.

3) Janet Foutty. “How Digital Transformation - and A Challenging Environment - Are Building Agility and Resilience.” Deloitte Insights, April 2021.

About the Authors

Tracey Johnson is a senior marketing manager at Analog Devices, where she leads a Digital Go to Market team, focused on the industrial automation market space. In 2003, Tracey graduated from the University of Limerick, Ireland, with a bachelor’s degree in electronic engineering. She joined ADI as a design evaluation engineer and has since held roles in applications and marketing.

Margaret Naughton is a marketing engineer at Analog Devices, where she works as part of a Digital Go to Market team, focused on the industrial automation market space. Since joining ADI in 2007, as a software developer, Margaret has held roles in CAD, engineering enablement, and marketing. She holds a bachelor’s degree in computer engineering and has a master’s degree from the University of Limerick.

■ Analog Devices www.analog.com

Add Bluetooth 5.3 to Edge IoT Designs

QUICKLY AND COST EFFECTIVELY

This article introduces the ultra-low-power STM32WBA52 MCU series from STMicroelectronics and shows how developers can use a BLE evaluation board, development tools, and application examples to get a BLE 5.3 wireless design up and running quickly. A brief look at programming and MCU wiring is included.

Author: Rolf Horn Applications Engineer DigiKey

Relentless competition puts pressure on Internet of Things (IoT) device developers to rapidly introduce new and innovative products while reducing costs and ensuring robust, low power, and secure communication. Traditional intelligent IoT end nodes comprise a microcontroller unit (MCU) to enable edge processing and a wireless IC for connectivity. Problems arise when design teams lack the radio frequency (RF) skills required for an effective solution. To complete, certify, and move their wireless IoT designs into volume production on time, developers need to make the development process more efficient.

One way to boost the efficiency of the development process involves using a lowpower MCU with an integrated Bluetooth Low Energy (BLE) wireless interface.

POWER-SAVING WIRELESS MCU WITH HIGH SECURITY LEVEL

Certified for BLE 5.3, the STM32WBA52 MCU series is a cost-effective solution that enables novice developers to quickly add wireless communications to their devices. Based on the Arm® Cortex®-M33 core with a 100 megahertz (MHz) clock and TrustZone technology, these microcontrollers provide a high level of security, protect data and intellectual property (IP),

and prevent hacks and device cloning. While the STM32WBA52CEU6 wireless MCU has 512 kilobytes (Kbytes) of flash memory and 96 Kbytes of static RAM (SRAM), the STM32WBA52CGU6 variant offers 1 megabyte (Mbyte) of flash memory and 128 Kbytes of SRAM. Figure 1 shows the functional scope of the IC in a 48 UFQFN package. Incidentally, up to 20 capacitive touch channels enable the operation of hermetically sealed devices (no mechanical keys are needed).

A rich STM32Cube ecosystem supports the implementation and programming of the BLE application. It includes the STM32 CubeIDE development environment, as well as tools like the STM32CubeMX peripheral configurator and code generator, the STM32CubeMonitorRF performance

© Credit:Peach_iStock

tester, and the STM32Cube.AI desktop and cloud versions for artificial intelligence (AI). A matching evaluation board, the NUCLEO-WBA52CG, simplifies prototyping and accelerates validation with many BLE sample applications and freely available source code.

DEVICE AND DATA SECURITY

The STM32WBA52 product line complies with the IoT security standards Platform Security Arm (PSA) Certified Level 3 and Security Evaluation Standard for IoT Platforms Assurance Level 3 (SESIP3).

Cyber protection is enhanced by the PSA security program based on security isolation, memory protection, tamper protection, and the MCUs’ Cortex-M33 with Arm TrustZone architecture. The Trusted Firmware for Arm Cortex-M (TF-M) complies with the industry standard PSA Certified Security Framework with PSA

immutable Root of Trust (RoT), including secure boot and secure firmware update (X-CUBE-SBSFU), cryptography, secure storage, and run-time attestation.

INTEGRATED RADIO MINIMIZES THE BOM

The integrated ultra-low-power radio module delivers +10 decibels referenced to 1 milliwatt (mW) (dBm) RF output power. It enables reliable communication over short distances (BLE 5.3) and long distances (Long Range) with data rates of up to 2 megabits per second (Mbps).

A deep standby low power mode reduces overall electrical power when radio communication is active. The STM32WBA MCUs can support up to 20 simultaneous connections.

Electrical performance characteristics of the radio module:

• 2.4 gigahertz (GHz) RF transceiver supporting BLE 5.3

• RX sensitivity: -96 dBm (BLE at 1 Mbps)

• Programmable output power, up to +10 dBm in 1 dB steps

• Integrated balun

SMALLER BATTERY DUE TO HIGHLY EFFICIENT ENERGY MANAGEMENT

The STM32WBA52 MCUs have many energy-saving technologies, including STMicroelectronics' Low Power Direct Memory Access (LPDMA) and flexible power-saving states with fast wake-up times.

Together, these features can reduce MCU power consumption by up to 90%, which translates to a significantly smaller battery or a longer battery life.

Electrical performance features of FlexPowerControl:

• 1.71 to 3.6 volt power supply

• 140 nanoampere (nA) standby mode (16 wakeup pins)

• 200 nA standby mode with real-time clock (RTC)

• 2.4 microampere (μA) standby mode with 64 Kbytes SRAM

• 16.3 μA stop mode with 64 Kbytes SRAM

• 45 μA/MHz run mode at 3.3 volts

• Radio: Rx 7.4 milliamperes (mA) / Tx @ 0 dBm 10.6 mA

Figure 1 A functional block diagram of the STM32WBA52 shows the integrated BLE 5.3 radio, flash and SRAM, and security support.

© STMicroelectronics

Figure 2

The MCUs process the data flow from the radio PHY to the GATT and GAP.

© STMicroelectronics

Additionally, Bluetooth 5.3 offers faster switching between low duty and high duty cycles, making it more energy efficient than previous versions.

ARCHITECTURE OF THE BLUETOOTH STACK AND DATA PACKETS

The single-core Arm Cortex-M33 MCUs in the STM32WBA52 are designed for the development of application firmware, including profiles and services on the BLE stack (controller and host). The MCUs process the data flow from the integrated RF module at the lowest physical layer (PHY) to the generic attribute profile (GATT) and generic access profile (GAP) (Figure 2). The GAP defines and manages advertising and connection, while the GATT defines and manages in/out data exchange.

BLE sends data packets that are defined as a fixed frame structure of a bit sequence. The length of the user data area can vary dynamically from 27 to 251 bytes.

BLE APPLICATION EXAMPLES

The online encyclopedia, STMicro-Wiki for STM32WBA MCUs, contains several application examples for different Bluetooth roles, including:

• Advert: BLE_Beacon

• Sensor: BLE_HealthThermometer, BLE_HeartRate

• Bridge: BLE_SerialCom

• Router: BLE_p2pRouter

• Data: BLE_DataThroughput, BLE_p2pServer & Multi Slave BLE_p2pClient

• RF-Monitor: BLE_TransparentMode,

• Firmware Update Over The Air: BLE_Fuota

Matching their own BLE project, device designers and programmers can flash the compiled binary from the corresponding GitHub project directory to the NUCLEO board and start the Bluetooth connection to a smartphone or desktop PC.

The required programmer software, STM32CubeProg provides reading, writing, and verification of device memory through both the debug interface and the bootloader interface.

RUNNING THE BLE EXAMPLE

“HEALTH THERMOMETER SENSOR”

The Health Thermometer Profile (HTP) is a GAP based low-energy profile defined by the Bluetooth Special Interest Group (SIG). It combines a Health Thermometer Collector and a Health Thermometer Sensor to connect and exchange data in different applications (Figure 3).

The Health Thermometer Sensor:

• Measures the temperature and exposes it via the Health Thermometer Service

• Contains the Device Information Service to be identified by the remote device

• Is the GATT server

The Health Thermometer Collector:

• Accesses the information exposed by the Health Thermometer Sensor and can display it to the end-user or store it on nonvolatile memory for later analysis

• Is the GATT client

After the Health Thermometer binary file is flashed into the NUCLEO’s MCU, the developer needs to follow the next steps to run the BLE application example:

Figure 3 BLE communication between the NUCLEO board as sensor/server and a smartphone as collector/client.

Table 1: GATT services and their UUID for the “Health Thermometer Sensor” GAP.

Using the Smartphone-App

1 Install ST BLE Toolbox on a smartphone. The app is used to interact with and debug ST BLE devices.

2 Power on the STM32WBA NUCLEO board with the Health Thermometer application flashed in.

3 Turn the smartphone Bluetooth (BT) on and scan BT devices available in the app. Select Health Thermometer and connect.

Using the Web browser interface

1 Ensure browser compatibility: on a desktop computer: Chrome, Edge, or Opera on a smartphone device: Chrome Android

2 Power on the STM32WBA NUCLEO board with the Health Thermometer application flashed in.

3 Activate Bluetooth on the computer.

4 Open the web page https://applible. github.io/Web_Bluetooth_App_WBA/ in the browser.

5 Click on the connect button at the top of the web page, then select HT_xx in the device list and click pair. The device is now connected.

6 Click on Health Thermometer to show the interface.

Table 1 describes the structure of the services of the Health Thermometer Sensor. The 128-bit long Universally Unique Identifier (UUID) distinguishes the individual characteristics and services.

The following JavaScript sequence from GitHub shows how the web browser interface filters the different GATT datathroughput characteristics (Listing 1). Tracing the BLE stack processes

Copy

[...]

The NUCLEO-WBA52CG embeds the STLINK/V3 in-circuit debugger and programmer, supporting the STM32 virtual COM port driver for communication with a PC via a serial interface.

// Filtering the different datathroughput characteristics props.allCharacteristics map(element => { switch (element.characteristic.uuid) {

case "00002a1c-0000-1000-8000-00805f9b34fb":

IndicateCharacteristic = element; // Temperature Measurement (TEMM)

IndicateCharacteristic.characteristic.startNotifications();

IndicateCharacteristic characteristic.oncharacteristicvaluechanged = temperatureMeasurement; break;

case "00002a1d-0000-1000-8000-00805f9b34fb":

ReadCharacteristic = element; // Temperature Type

readTemperatureType(); break;

case "00002a1e-0000-1000-8000-00805f9b34fb":

NotifyCharacteristic = element; //Immediate Temperature

NotifyCharacteristic characteristic.startNotifications();

NotifyCharacteristic.characteristic.oncharacteristicvaluechanged = notifHandler; break;

case "00002a21-0000-1000-8000-00805f9b34fb":

ReadWriteIndicateCharacteristic = element; // Measurement Interval

readMeasurementInterval(); break;

default:

console.log("# No characteristics found.."); }

});

[...]

Listing 1: This JavaScript sequence filters the different GATT datathroughput characteristics from Table 1.

Figure 4

Programmers can add their own GATT content to the framed code files (left); these files generate the GATT services (right).

© GitHub, STMicroelectronics

Copy [...] void HTS_Init(void)

{ [...]

/* TEMM, Temperature Measurement */ uuid.Char_UUID_16 = 0x2a1c; ret = aci_gatt_add_char(HTS_Context.HtsSvcHdle, UUID_TYPE_16, (Char_UUID_t *) &uuid, SizeTemm, CHAR_PROP_INDICATE, ATTR_PERMISSION_NONE, GATT_DONT_NOTIFY_EVENTS, 0x10, CHAR_VALUE_LEN_VARIABLE, &(HTS_Context.TemmCharHdle)); if (ret != BLE_STATUS_SUCCESS)

{

APP_DBG_MSG(" Fail : aci_gatt_add_char command : TEMM, error code: 0x%2X\n", ret);

} else

{

APP_DBG_MSG(" Success: aci_gatt_add_char command : TEMM\n");

}

/* USER CODE BEGIN SVCCTL_InitService2Char1 */

/* USER CODE END SVCCTL_InitService2Char1 */ [...]

} [...]

Listing 2: The initialization sequence from file hts.c generates the GATT characteristic TEMM

Any software terminal can open this serial communication port to show the short text messages generated in the code by the function APP_DBG_MSG.

The traces within the project need to be enabled in the file app_conf.h #define CFG_DEBUG_APP_TRACE (1) Alternatively, the smartphone app "SE BLE Toolbox" offers a trace function on tab <Application Log>.

Programming BLE 5.3 applications

For programming the STM32WBA52 MCUs, STM has put together the

Figure 5

©

STM32CubeWBA-Package consisting of a hardware abstraction layer (HAL), lowlayer application programming interfaces (APIs) and CMSIS, File system, RTOS, BLE/802.15.4, Thread, and Zigbee stacks, as well as examples running on STMicroelectronics boards. Project structure setups for all three development environments (IDEs), such as IAR Embedded Workbench for Arm (EWARM), Keil MDK-ARM, and STM32CubeIDE, are included in each NUCLEO-WBA52CG BLE application example

In the case of the Health Thermometer example, only specific files from the project directory tree (frame in Figure 4 left) generate the GATT services. The two routines, "Health Thermometer Service” (hts) and "Device Information Service” (dis) from Table 1, run in parallel (bottom right of Figure 4).

Programmers can use the source code for their own projects and extend it with their GATT content in the areas marked with USER CODE BEGIN / USER CODE END (Listing 2). The initialization sequence from file hts.c generates the GATT characteristic Temperature Measurement (TEMM) carrying the UUID 0x2A1C.

EXTERNAL COMPONENT REQUIREMENTS

The STM32WBA52 wireless MCU requires only a few external components for basic operation with Bluetooth functionality. These include capacitors for the voltage supply, a crystal oscillator, a printed circuit board (pc board) antenna with impedance matching, and a harmonic filter (Figure 5).

CONCLUSION

Developers of wireless IoT devices need to shorten design cycles and lower costs to compete in a rapidly evolving market. However, RF design is challenging. The STM32WBA52 MCU, with its integrated BLE 5.3 interface, allows developers to get to market quickly and cost-effectively. The pre-programmed BLE stack and several BLE application examples form a programming template for custom projects where GATT contents are easily inserted.

■ DigiKey www.digikey.com

For Bluetooth, the STM32WBA52’s RF terminal connects to an impedance-matching network, a harmonic filter, and an antenna. ©

New Powerful Single-Chip RZ/V2H MPU for Next-Gen Robotics with Vision AI și Real-Time Control

Recently Renesas has expanded its popular RZ Family of microprocessors (MPUs) with a new device targeting high-performance robotics applications. Offering the highest levels of performance within the family, the RZ/V2H enables both vision AI and real-time control capabilities. The new RZ/V2H MPU will also be demonstrated at the Renesas booth at this year’s Embedded World in Hall 1, Stand 234 (1-234). We had the opportunity to talk to Keigo Kawasaki, Director of Marketing from Renesas, about the new addition to the RZ family and its unique new features for the robotics application to the further evolution of AI.

Keigo Kawasaki has more than 25 years of experience in product planning, solution development, business development, and partnership/ecosystem development for SoCs/MPUs. In his current position he focuses on the Industrial MPU area. He began his career at NEC in the field of mobile SoC and digital AV.

More semiconductor companies are now offering AI processors. What sets Renesas apart from the competition?

There are three key differentiators:

• AI accelerator “DRP-AI3” with “Pruning” technology – Pruning is a hardware-based approach to enable lightweight AI models and enhance AI computing efficiency. This also resulted in 10 TOPS/W power efficiency, a 10-fold improvement over previous models.

• Acceleration of image processing in addition to AI acceleration – To increase the performance of the entire imaging system, the RZ/V2H includes the OpenCV Accelerator, along with the free-of-charge OpenCV acceleration library.

• In addition to the quad 1.8 GHz Arm Cortex-A55 for application processing, the device delivers robust real-time control performance with dual-core 800-MHz Cortex-R8 processors and a Cortex-M33 processor for handling less intensive tasks such as data retrieval from sensors. Renesas’ RZ/V2H is the only heterogeneous AI processor that is equipped with all three (A, R, M) Cortex products from Arm.

What are the challenges for implementing vision AI, especially in embedded systems? What is Renesas’ solution?

Heat generation is a major challenge in embedded systems. Since high-performance processors generate heat, engineers often face challenges to offset the heat by either lowering performance or adding heat-dissipating components, which in turn increases cost and system size. With an AI power efficiency of 10 TOPS/W, the Renesas RZ/V2H can easily realize high-performance vision AI applications without cooling fans.

What applications require real-time image processing?

Industrial robots for factory automation and service robots for restaurants and commercial facilities require real-time image processing capabilities. These are robots that can recognize surrounding objects and obstacles in real time and move autonomously. Additionally, drones and small transportation vehicles also need to think independently and operate in real time. The RZ/V2H is ideal for these applications.

What kind of feedback did you receive from customers?

Many customers have already decided to adopt our AI modules for industrial applications and small modules for HSR (Human Support Robot). There are also more than 40 customers who are considering our products. The decisive factor in all of these discussions is the fact that the RZ/V2H can significantly reduce heat generation.

What accelerates the widespread adoption of vision AI applications?

What is Renesas’ strategy?

One major challenge is that engineers often struggle to utilize AI effectively due to the requirement for specialized AI skills. Renesas offers a number of AI application libraries free of charge to address customers' challenges.

Tell us about your future roadmap. On the technology front, we will continue to pursue TOPS/W to improve power performance. In the future, we expect that embedded devices will have applications

that require more computing performance, such as generative AI. In terms of productization, we will continue to address the demands of our customers and market.

What are the benefits of

Renesas’ proprietary DRP technology?

DRP (Dynamically Reconfigurable Processor) can execute applications while dynamically switching the circuit connection configuration of the arithmetic units on the chip at each operating clock according to the content to be processed. Since only the necessary arithmetic circuits are used, the DRP consumes less power than with CPU processing and can achieve higher speed. Furthermore, compared to CPUs, which experience degraded performance caused by frequent external memory accesses due to cache misses and other factors, the DRP can build the necessary data paths in hardware. This minimizes performance degradation and reduces variation in operating speed (jitter) due to memory accesses.

The DRP also has a dynamic reconfigurable function that switches the circuit connection information each time the algorithm changes, enabling processing with limited hardware resources, even in robotic applications that require processing of multiple algorithms. The DRP is particularly effective in processing streaming data such as image recognition, where parallelization and pipelining directly improve performance.

What are the benefits of the heterogeneous architecture in which DRP-AI3, DRP, and CPU operate together seamlessly?

Service robots, for example, require advanced AI processing to recognize the surrounding environment. On the other hand, algorithm-based processing that does not use AI also needs to decide and control the robot's behavior. However, current embedded processors (CPUs) lack sufficient resources to perform these various types of processing in real time. Renesas solved this problem by developing a heterogeneous architecture technology that enables the AI accelerator (DRPAI3), OpenCV accelerator (DRP), and CPUs to work together.

The DRP AI3 accelerates vision AI processing. Renesas has applied its proprietary DRP technology to develop the OpenCV Accelerator that speeds up the processing of OpenCV, an open-source industry standard library for computer vision processing.

The resulting speed improvement is up to 16 times faster compared to CPU processing. The combination of the DRP-AI and the OpenCV Accelerator enhances both AI computing and image processing algorithms, enabling the power-efficient, realtime execution of Visual SLAM used in applications such as robot vacuum cleaners. On the other hand, programs such as robot behavior decision-making and control require precise processing in response to changing conditions and changes in the surrounding environment. To do this, CPU software processing may be more suitable than hardware processing such as the DRP. It is important to distribute processing to the right places and operate in a coordinated manner. Renesas’ heterogeneous architecture technology allows the DRP and CPU to work together.

Does Renesas have plans to develop a Neural Processing Unit (NPU)?

“NPU” is a generic term for hardware IP specialized for AI processing, and DRP-AI is a type of NPU.

What are the new technologies

DRP-AI3 uses in the RZ/V2H?

DRP-AI3 introduces high-speed and lowpower methods that support major AI model lightening methods. Specifically, the following lightweight methods are supported:

1) Quantization: Lower-bit weights for neural network weight information (weight) and input/output data (feature map) for each layer. Change from 16-bit floatingpoint arithmetic in conventional DRP-AI to 8-bit integer arithmetic (INT8).

2) Branch pruning: A technique to skip calculations by setting weight information (branches) that do not affect recognition accuracy to zero.

More detailed technical content was presented at the ISSCC 2024 (International Solid-State Circuits Conference 2024), a prestigious international conference on semiconductor circuits, held from February 18 to 22, 2024. The press release has been issued on Feb 22, 2024.

Are there any winning combinations / reference designs for the RZ/V2H already available?

Renesas has developed the “Visual Detection Single Board Computer” that uses camera images to identify its surroundings, and to determine and control its movements in real-time. This solution combines the RZ/V2H with power management ICs and VersaClock programmable clock generators to support powerefficient industrial robots and machinery. Its efficient design eliminates the requirement for an additional cooling fan, keeping the solution BOM and size down. This winning combination will be displayed at the Renesas booth at embedded world 2024 in Hall 1, Stand 234 (1-234).

Tell us about the device offerings from the RZ/V series.

The RZ/V series is MPUs that incorporate an accelerator called DRP-AI. We offer a scalable lineup from 0.5 TOPS up to 80 TOPS with the same architecture.

Many thanks!

■ Renesas www.renesas.com

Advantages through proximity

Author: Johannes Gasde, Corporate Product Manager Embedded & Wireless Rutronik

Companies utilizing European components in their embedded designs often enjoy greater resilience compared to those dependent on suppliers from the USA or the Far East. This is not only due to shorter transport routes, reliable political systems, and the often-preferred supply of customers on the same continent. Proximity and thus usually better communication between component or system providers, distributors, EMS, and companies also often make the decisive difference. Especially in times of higher volatility, it is indispensable to coordinate requirements, capacities, and delivery capabilities in the best possible way. With boards, numerous modules and systems, processors, flash memories and DRAM modules, as well as accessories, Rutronik has everything needed to create embedded designs. For the majority of components – with the exception of only the CPU – the linecard also includes an established supplier based and with production facilities in Europe. Reason enough to introduce them here.

Events such as the war in Ukraine, extreme weather conditions, and COVID-19 have shown how fragile global supply chains can be – and increasingly are. This makes systems and components from Europe all the more important.

MOTHERBOARDS FROM KONTRON

Kontron develops and produces a comprehensive portfolio of high-quality, durable, and competitive motherboards in Germany. They support the latest processors and platform chipsets and are available in Mini-STX, Mini-ITX, μATX, and ATX form factors. With their design for 24/7 continuous operation, a wide temperature range of 0 °C to 60 °C, and availability of up to seven years after market launch, they are suitable for a broad range of even demanding applications, from industrial automation, POS/POI and kiosk applications, digital signage, and casino gaming to medicine, video surveillance, and transportation.

Rutronik, together with its franchise partner Kontron, also supports its customers with accessories such as package kits or add-on cards, as well as valuable services like detailed documentation, professional life-cycle management, and customization tools.

COMPUTER-ON-MODULES

AND SBCs FROM SECO

Seco combines all the processes and services required for the production of boards and electronic systems for various application areas at locations in Italy and Germany.

Production at its roughly 9,000 m2 headquarters in Arezzo (Italy) is focused on both energy efficiency and innovation. In Hamburg, production, development, administration, sales, and marketing are located at the company’s approx. 8,000 m2 plant. At its third large location in Wuppertal, close proximity between development and production enables rapid and straightforward implementation of prototypes, pre-series products, and small series.

Seco's production installations are equipped with machines for SMT and THT PCB assembly as well as stations for washing, conformal coating, depaneling, and BGA rework.

© Popel Arseniy/Shutterstock

Critical processes in the production of electronic components can thus be comprehensively monitored by the supplier, who can respond quickly and effectively in the event of problems.

MODULES AND SBCs FROM F&S ELEKTRONIK SYSTEME

Founded as an engineering company in 1990, F&S Elektronik Systeme started producing its own modules in 1998. To date, every single module is produced in StuttgartVaihingen on cutting-edge manufacturing equipment, functionally tested, and subjected to strict quality and compliance testing (ISO 9001, ISO 13485). In addition, the systems are characterized by scalable processing power and long-term availability of up to 15 years. Over 20 hardware and software developers provide fast and qualified support.

Roughly, 2,600 m2 of space is available here for chip-on-board (COB) and surfacemount device (SMD) production.

Swissbit’s industrial memory and security products are characterized by long-term availability and high reliability. They are thus also suitable for demanding applications in the industry, NetCom, automotive, medicine, fiscal, and IoT sectors. Customers also receive appropriately optimized products for specific requirements.

MEMORIES FROM GOODRAM INDUSTRIAL

Goodram Industrial is a brand of the Polish supplier Wilk Elektronik. It offers memory cards, USB flash drives, SSDs, and memory modules for use in industrial applications that often operate in extremely harsh conditions.

© Swissbit

IT ASSEMBLY IN GERMANY BY EXTRA COMPUTER

With its own brands exone, Calmo, and Pokini, Extra Computer covers the entire field of computer systems: embedded box PCs, panel PCs, 19” industrial servers, boxed IPCs, and notebooks. At its main location in Giengen-Sachsenhausen, IT hardware is assembled by hand and on state-of-the-art production lines. The certified quality (DIN EN ISO 9001) of the production and sales processes as well as comprehensive quality controls for each individual system guarantee a consistent design and the outstanding value of all the systems.

STORAGE AND SECURITY COMPONENTS FROM SWISSBIT

The supplier of storage, security, and embedded IoT components, headquartered in Switzerland, manufactures up to three million items per month at its production facility in Berlin, which the company put into operation at the end of 2019.

system certification for the production and sales of DRAM modules and flash memories) ensure innovative and high-quality products that Wilk also adapts to specific customer requirements.

Among other services, technical support includes the long-term availability of components, functional and environmental diagnostics, and individual training and consulting.

OTHER SUPPLIERS FOR ACCESSORY PRODUCTS

Rutronik also collaborates with other European-based suppliers who specialize in accessory products.

This means that embedded designs can also be implemented with cooling technology (EKL, HSM Zamecki), packages (Emko), and power supplies (Recom) “Made in Europe”.

SUPPLY AND SUPPORT BY RUTRONIK

Rutronik maintains good working relationships with all suppliers, which have grown over many years through personal contacts and joint technical support.

In addition to ensuring on-demand supplies, Rutronik’s technical experts in the Embedded & Wireless segment enhance the supplier service by conducting their own validated memory tests (MemTest86) for various motherboard-memory combinations. This means that customers can rely on their functionality.

Wilk Elektronik manufactures the Goodram Industrial brand DRAM modules in southern Poland.

In-house development, a production line in Poland, which was put into operation in 2003, 30 years of market and production experience, and advanced quality control procedures (ISO 9001 quality management

There are so many good reasons to choose “Made in Europe”.

■ Rutronik

www.rutronik.com

State-of-the-art production by Swissbit in Berlin.

© Wilk Elektronik

Bringing Innovation to Life

IN THE MEDICAL TECHNOLOGY INDUSTRY

Author: Shawn Luke Technical Marketing Engineer DigiKey

Our society’s aging global population, coupled with the rise in chronic diseases among younger populations, is putting significant pressure on healthcare systems. The need for new solutions is fueling innovation and digitalization across the industry. New advances in data analytics through artificial intelligence and machine learning are changing the future of the MedTech industry – a market size predicted to reach $996.93 billion by 2030.

So, what is happening behind the scenes and how are modern healthcare products getting smarter and more efficient? The team at DigiKey, along with several partners, are working tirelessly to create and distribute cutting-edge products, parts, components and solutions that improve individual health journeys and save lives. A key aspect of this evolution is the involvement of wearable sensors, edge

Technological advancement in the healthcare industry, particularly with medical devices, is enabling faster and more accurate diagnoses and treatments for patients around the world. From wearables to AI-powered innovation, medical technology has opened the door to more personalized and real-time care.

computing, and wireless devices to create seamless connection points useful for the entire medical ecosystem of doctors, nurses, engineers, designers, sourcing professionals, patients, families, and others.

WEARABLES AND PERSONALIZED TREATMENT

Creating and launching a new medical device is no easy feat and overcoming stress testing individual components and filing for regulatory approval are just two of the hurdles. But many are leading the way and successfully bringing user-friendly medical devices to the market to empower people to better understand and regulate what’s happening in their bodies. These devices use key technologies, including IoT functions, sensors, and wearables, to help patients monitor their vital signs, such as percentage of blood oxygenation, heart rate, blood pressure, and more.

It is estimated that one in three adults will own a wearable device by 2025. Real-time knowledge is insightful and powerful for making lifestyle changes and maintaining good habits.

This technology is also creating a new model of care where so much more is being done at home. Behind all of this are wireless, sensor, and semiconductor products that are driving the collecting, connecting, and sharing of data and insights.

As medical technology continues to evolve, the personalization of treatment will get better, too. Physicians will more regularly review data remotely and offer recommendations for treatments and even helpful home products. For example, an adjustable bed is now on the market that can sense when someone is snoring, and the bed automatically changes its

incline to try and help reposition the person and open their airways more. This may be a key solution for those who struggle with sleep apnea.

EDGE PROCESSING

Making personal health data and insights immediately accessible to patients is a result of edge processing which in many cases includes AI and machine learning models. Semiconductor manufacturers are highly focused on this right now. It allows insights to occur closer to the patient and requires less bandwidth and data to be exchanged with the cloud.

Edge computing brings data processing, analysis, and storage closer to the source, such as a patient’s cell phone, watch or iPad. Edge computing works as a complement to the cloud. This strategy can help both patients and health systems optimize the collection, storage and analysis of data—which requires the consideration of privacy, storage space, and costs. But above all, the desire for immediate access to information is the real motivator.

Semiconductor suppliers such as NXP, Microchip, and STMicroelectronics are providing the path for real-time diagnosis and personalized treatment. For instance, NXP has a long history of providing rigorously tested products to verticals, including the healthcare industry. Their products integrate functions, including how to process information at the far edge, along with security, computing, and connectivity measures. They are one of the leaders behind products in edge processing and bringing realtime data to people’s fingertips.

From a power standpoint, a supplier offering drop-in solutions with medical certifications like RECOM Power can save design time, energy and cost. Medical grade AC/DC power supplies and DC/DC converters that are fully tested through rigorous agency certifications or made for the rigor of a medical setting can expedite medical technology development time. Buying appropriately suited medical power solutions will become increasingly advantageous as applications get smaller and require voltage levels to remain safe for providers and patients. For patients, the easier they can access their personal health data, the better. Someone who wants to actively monitor how long or deep they are sleeping each night, can collect those data points continuously and have them pushed to their preferred device through edge computing. Knowledge is power, and today’s technology is proving you don’t have to be a doctor or nurse to review data and understand some of the things happening in your body on a daily basis. Wireless devices and sensors keep improving, allowing patients to self-serve more.

WIRELESS MODULES AND DEVICES

The acceptance and popularity of wireless devices grew exponentially when the COVID-19 pandemic necessitated remote access and, in turn, spotlighted many other benefits, including more efficient healthcare delivery and continuous patient monitoring.

DigiKey Highlights New Resources for Makers at Hackaday Europe 2024

DigiKey, a leading global commerce distributor offering the largest selection of technical components and automation products in stock for immediate shipment, has announced its sponsorship of Hackaday Europe 2024, held April 13-14 in Berlin.

The 5th annual Hackaday Europe conference will feature talks, demos and workshops exploring unique, cutting-edge and worldchanging topics around hardware creation, such as hardware, engineering, creativity in technical design, product design, prototyping and more.

DigiKey team members will be handing out the famous DigiKey PCB rulers and other great swag at the show.

“DigiKey is excited to sponsor Hackaday Europe and showcase our newest offerings of products, content and tools for hardware enthusiasts,” said Kevin Walseth, technical marketing manager at DigiKey. “We are a proud partner of Hackaday and can’t wait to get technical with attendees about what they’ve been working on and how we can help their designs.”

“We are excited to welcome back our amazing community of engineers, designers, hardware enthusiasts, scientists, educators and everyone in between to Berlin for the 5th annual Hackaday Europe,” said Majenta Strongheart, director of DesignLab for Supplyframe. “We have a wealth of brilliant speakers lined up and look forward to hacking, learning, show and tell and mutual inspiration throughout the event.”

Each attendee will receive a custom Vectorscope electronics badge to hack on during the conference and beyond, and there will be a badge hacking ceremony at the end of the conference to show off cool and unique hacks.

DigiKey is a long-standing Hackaday partner, powering quarterly hardware design contests, sponsoring the Supercon event and Hackaday Prize, and much more.

For more information about Hackaday, visit hackaday.com

For more information about DigiKey’s maker community, visit DigiKey’s Maker.IO site.

■ DigiKey | www.digikey.com

Heart monitors and continuous blood glucose level monitors are examples of healthcare devices that have gained widespread acceptance in improving patient outcomes and remote patient management.

This all feeds into the Internet of Medical Things (IoMT), where networks of patients with portable and/or wearable medical devices and sensors and their corresponding healthcare systems and providers are connected through the Internet. IoMT devices help automate data transfer, thereby reducing human errors.

The wireless concept here is important because it allows for near-field and/or short-range communication. Wireless modules also allow a broader aggregation of data in the cloud, which enables practitioners to remotely monitor patients and access a wider sample for benchmarking and diagnosing. Using anomaly detection, certain events or triggers throughout a patient’s day can select periods where more verbose diagnostic data can be helpful and provide extra data for those events. Having all this data available in the cloud to a patient’s full bench of providers is instrumental in more complete and accurate patient management.

OPENING ACCESS TO PATIENT CARE AND LOOKING AHEAD TO THE FUTURE

Medical technology is not only personalizing healthcare, but it’s also increasing access to it. By lowering burdens on patients and physicians, more people will be able to use and enter the healthcare system. The AI and data revolution is reimagining the future of care, surgery, therapy, medication usage, and more. It will be exciting to see where we’re at ten years from now.

While the medical technology industry continues to face significant challenges related to regulatory requirements, cybersecurity issues, recalls and lawsuits, leaders in the industry are navigating and overcoming these areas to push innovation forward like never before.

The impact of IoT will continue to grow as more medical sensors are developed and drive more secure connections to deliver sensitive health data.

As device usage keeps increasing among the general population, there will be more data to store and make sense of, which will spur additional AI models doing the detection work that doctors and specialists are currently charged with today.

Using devices for continuous monitoring is already showing the deep and remarkable impact personalized healthcare can make.

At DigiKey, we understand the importance of having the right products available to enable technology and innovation in the healthcare industry, where the stakes are high when it comes to patient care. We have a wide selection of medical technology products, along with application details, articles and technical resources, which keep the smartest minds in the industry working with us.

Learn more about our work and partnerships by watching our new MedTech Beyond video series.

DigiKey , is recognized as the global leader and continuous innovator in the cutting-edge commerce distribution of electronic components and automation products worldwide, providing more than 15.3 million components from over 2,900 quality name-brand manufacturers.

■ DigiKey www.digikey.com

What’s driving the use of 5G precise positioning technology and why is it important?

Author: Jonathan Borrill Anritsu Corporation

The fifth generation mobile network 5G is expanding into new industries as well as new technology areas because of the many benefits it offers in terms of positioning accuracy. Whereas 2G, 3G and 4G were mostly focused on consumer services such as voice, messaging and mobile browsing, 5G has been proving ideal for applications where connected devices need the level of accuracy or coverage that may not be available using global navigation satellite system (GNSS) positioning. These include autonomous vehicles, robots, Internet of Things (IoT) systems, indoor packaging, warehousing and ‘smart’ manufacturing facilities.

5G makes this possible by using precise positioning technology (PPT) through the third generation partnership project (3GPP) which encompasses telecommunications standards organisations around the world.

While 3GPP specifications cover cellular telecommunications technologies, including radio access, core network and service capabilities, we can expect the PPT in ‘local 5G’ networks to be used for industrial applications. Designed to be the global standard for the air interface of 5G networks, 5G New Radio (NR) is a new radio access technology (RAT) developed by 3GPP for 5G applications. The aim is to use 3GPP signalling in the 5G network to enhance the performance of position calculation. This involves using existing signals in the 5G network as well as introducing some specific new signals which directly support the enhanced positioning capability.

The 5G positioning capabilities being introduced as 3GPP precise positioning features can supplement GNSS to enhance accuracy and/or improve measurement times.

In addition, it can provide position information when GNSS is simply not available, such as indoor environments, factories, tunnels, underground car parks, ‘urban canyons’ and so on.

Among those looking at adopting 5G PPT are mobile network operators (MNOs), infrastructure vendors, chipset vendors, IoT module vendors, and the automotive and smart factory ecosystems mentioned earlier.

THE FEASIBILITY OF TECHNICAL DEPLOYMENT

MNOs are currently in the process of estimating network deployment schedules and, although it can appear that MNOs follow the establishment of capability in the ecosystem, they are often the main driving force that creates demand within infrastructure vendors and device vendors. Once the capabilities are established within 3GPP specifications, and trials have proven the feasibility of technical deployment, the key issue for launch will be the business model suited to each industry segment.

Infrastructure vendors welcome the fact that no new physical entities are required with 5G PPT – which is built around new signalling capabilities in the radio access network (RAN) and new software functions in the core network – so feature development is typically software-based. The vendors are currently setting up demonstrators and trials to test and prove the new features before a widespread commercial launch. Once the 3GPP specifications are fixed for each release, network capability will be driven by the MNOs’ required time to market. Chipset vendors have started to demonstrate the capability and ‘proof of concept’ for 5G PPT based on 3GPP Release 16 – which was released in July 2020 – and are engaging industry verticals with trials and evaluations. Again, as with infrastructure vendors, the features are mainly software driven. For RAN-supported features the chipset is mainly concerned with the measurement and reporting of the 5G NR position signals and measurements, with the focus on testing core functionality, standards compliance and basic performance in terms of location accuracy, time to fix and power consumption.

COMPLETE MODULE SOLUTION

IoT module vendors have concentrated on integrating the cellular chipsets, GNSS functions and other sensor data into a complete module solution that can be deployed in single or multiple use cases. While the critical capability of 5G NR positioning is already provided by chipset vendors, IoT module vendors are looking more towards overall data integration and achieving the required performance levels and control interfaces to make the function useable and attractive to the various vertical industry sectors.

One vertical – the automotive sector – is currently evaluating 5G NR PPT to enhance the position accuracy in areas with poor GNSS coverage, with the aim of supporting autonomous driving and vehicle-to-everything (V2X) safety applications. Of course, autonomous driving use cases will require high position accuracy, for example to locate a vehicle in the centre of a designated lane, but in many scenarios GNSS can’t provide this. That’s why 5G NR is being evaluated as part of the overall sensor fusion capabilities to provide enhanced position accuracy as a supplement to GNSS.

The industrial smart factory sector also has a clear interest in 5G NR precise positioning, especially in terms of providing accurate positional information inside a plant or warehouse building where GNSS coverage may not be available.

As the smart factory ecosystem currently evaluates the use of 5G NR for private 5G networks to provide wireless connectivity, it is a very attractive proposition to add precise positioning to this network capability.

Similarly, the large bandwidth provided by a 5G network could offer better multipath resolution and, therefore, high accuracy for measuring distances, which again could contribute to improving the accuracy of positioning measurements. Finally, single infrastructure handling positioning and telecommunication functions will not only help in lowering the overall infrastructure cost but could open up the possibility of a number of new geo-information applications.

‘STAND-ALONE’ POSITIONING

By operating as a ‘stand-alone’ positioning capability, 5G positioning will inherit many advantages of the 5G infrastructure that could potentially boost its accuracy. These include large cell site density which makes better positioning accuracy possible through many diversified anchor points being available for generating and processing positioning.

Another advantage is the deployment of massive multiple input, multiple output (MIMO) and beamforming, which could enhance the direction accuracy for algorithms like Angle of Arrival (AoA) and Angle of Departure (AoD).

The use of high-frequency channels by 5G networks could also contribute to better accuracy through reduced channel sparsity due to better array gains.

All these features will enable 5G positioning to create new opportunities in industrial asset tracking and commercial automation applications, essential in creating the Industrial IoT (IIoT) capability that will allow business owners to monitor and locate workers, assets and tools in real-time with a very high level of accuracy. Coupled with IIoT software platforms, these features should enable businesses to increase automation and enhance the efficiency of their factory processes.

A 2021 survey from ABI Research found that just over 50% of companies in five related industry verticals – healthcare, manufacturing, warehouse, transportation, oil & gas – planned to deploy realtime location services within the next five years, compared to a deployment rate at the time of just 13%.

SIDELINK POSITIONING

At the time of writing, 3GPP is studying and defining topics for expanded and improved positioning, particularly in terms of Sidelink positioning/ranging, improved accuracy, integrity, power efficiency and RedCap (reduced capability) positioning.

The automotive industry is especially interested in the Sidelink positioning feature because it can provide enhanced local information and positioning capability in scenarios where GNSS coverage isn’t available. The RedCap feature enables lower cost and lower specification devices and it is thought that the enhanced positioning capability provided by the 5G network can be of specific value for IoT applications.

Several industry bodies in the automotive industry are working to provide requirements and technology for 5G PPT. Organisations such as SAE (an automotive industry group based in the USA) and 5GAA (car OEMs, network operators and related supply chains) provide inputs that create requirements for the development of 5G features in the 3GPP specifications. The industry activity also includes ETSI (European Technical Standards Institute), leading in the area of automotive ITS standards for Europe, and RTCM (Radio Technical Commission for Maritime Services), which provides US standards for differential GNSS systems where a supplementary signal from a known precise location is used to enhance GNSS positioning capability.

EXPECTED REFERENCE SIGNALS

A vector signal analyser (such as the Anritsu MS2850A) can be used to capture the output of a 5G transmitter and display the contents of each frame or resource block. The specific resource elements relating to the expected reference signals can be checked for correct power level and format.

For user equipment (UE) measurements and reports, a network simulator (such as the Anritsu MT8000A Radio Communication Test Station) can be used to generate the downlink signal containing the relevant positioning reference signals with a known power level and position in the resource blocks. Control plane messages can then be configured and sent from the simulator to the UE to instruct it to make positioning measurements and report them back to the gNodeB (gNB) base station.

The simulator will then receive the measurement reports from the UE and verify that the contents of the measurement report are correct and correspond to the downlink positioning reference signal conditions that were created. These conditions include power level, AWGN (additive white Gaussian noise) level and timing.

In addition to functional testing, the UE can be verified using protocol conformance test procedures. These are a standardised set of protocol message sequences that can verify the correct format and sequence for messages sent to and from the UE.

There is also a set of conformance test procedures that can be used to verify the accuracy of the different measurement procedures.

‘REAL LIFE’ SCENARIOS

There are other functional tests that are specified by various industry bodies, such as the Open Mobile Alliance (OMA) as well as MNOs, to simulate ‘real life’ scenarios for the system to provide accurate location information.

These scenarios usually extend the scope of the UE testing to include further variations on GNSS signal conditions and network conditions to cover use cases beyond those of 3GPP conformance testing. This is usually done to cover scenarios and use cases which are specific to the MNO or to the specific network configuration they have chosen to deploy.

It's clear then that 5G is ideal for applications where high accuracy levels are required and where its precise positioning technology is superior to anything offered through GNSS positioning. Over the coming years, a wider range of industries will find themselves benefiting from the many benefits of 5G PPT, resulting in substantial improvements in accuracy and efficiency.

■ Anritsu Corporation

www.anritsu.com

Robotic Security Use Cases and Implementation

FOR A SECURE FUTURE

Author: Manoj Rajashekaraiah, Principal Engineer Analog Devices

In our previous article “Ensuring a Secure Future for Robotics: The Role of Cybersecurity”, we offered a comprehensive overview of the security challenges faced by robotic control systems. We highlighted the criticality of adhering to industrial security standards in robotics and explored the essential security capabilities necessary to fortify the protection of robotic control systems.

Additionally, we provided a preview of how Analog Devices’ security products could be utilized to implement a specific robotic security use case.

In this article, we will provide an overview of the components that constitute an industrial robot/cobot. It’s worth noting that many of these similar components are also commonly used in autonomous mobile robots (AMRs) and pick-andplace systems. Subsequently, we will explore various robotic security use cases, showcasing how ADI’s security products simplify the implementation of security in these diverse robotic control systems.

Building Secure Robotic Control Systems: Essential Technical Capabilities and Development Approach

We are revisiting this section from the previous article for a better understanding of key technical capabilities and technologies required to implement secure robotic control systems, which include:

• Secure authentication: Integration of secure authenticators to verify device/ component identity.

• Secure coprocessors: Utilization of dedicated hardware for secure storage and cryptographic operations.

• Secure communication: Implementation of encrypted protocols for protected data exchange.

• Access control: Enforcement of granular permissions to restrict unauthorized system access.

• Physical security measures: Incorporation of measures to protect against physical tampering.

In addition to these aspects, system developers must adopt a structured approach to secure development, including requirements gathering, threat modelling, secure design, implementation, testing, certification, and maintenance.

Component Name Description

Sections The central physical component, several sections are interconnected using joints and driven by motors. The arm enables precise movements.

Joint Two sections are interconnected using a joint and the joint has a motor and motor controller, which controls the movement of the section connected to it. Sometimes only the motor is kept in the joint and the motor controller itself is outside of the joint in industrial robots.

Robot controller Serves as the central intelligence of the robot, coordinating kinematic movements and actions. It enables communication from the controller to various joints and the end effector. The controller itself connects to the external world using industrial communications protocol like EtherCAT® PROFINET®.

End effector Tooling attached to the robot arm can carry out actions like gripping, welding, cutting, etc. The end effector may have sensors that directly interact with the cloud and there are cases where the end effector directly connects to the robot controller.

Programming interface Allows operators to teach and configure robot actions. (teach pendant)

Programmable logic Can be used in conjunction with a robot controller to enhance a robotic system’s automation and controller (PLC) control capabilities. A standalone robotic system might not connect to a PLC.

Following a secure development life cycle (SDL) ensures security from the start.

An Overview of Components in Industrial Robots and Cobots

Figure 1 shows typical components associated with the operation of industrial robots/cobots. Table 1 gives a quick overview of the different components.

ROBOTIC SECURITY USE CASES: Harnessing ADI’s Expertise and Products for Design and Implementation

Trusted PLC Operation and Gateway Protection

The combination of PLCs and robotic controllers offers precise control in factory automation setups, enabling finegrained control over various processes. In recent years, advancements in robotic technology have led to the development

of integrated controllers that possess PLC-like functionality. Ensuring the reliability and security of PLC operation is of utmost importance when it comes to maintaining the safe operation of a factory automation setup. See Figure 2.

Usage of devices like the MAXQ1065 (the ultra low power cryptographic controller with ChipDNA® technology for embedded devices) within PLCs can support the following use cases:

• Secure identification and clone prevention of the PLC modules.

• Secure boot and firmware download.

• Asymmetric key mutual authentication between PLC modules and PLC servers.

• Establish secure communication session with ECDH key exchange.

• Use of AES for encryption and decryption of network packets.

NOTE:

ChipDNA technology harnesses unique traits of electronic components to generate a secure cryptographic key. This key isn’t stored in memory or any fixed state, greatly enhancing protection against cyberattacks.

Direct Node to Cloud Security

Node-to-cloud communication (see Figure 3) in robotics enables several functionalities such as remote monitoring, data analysis, software updates, etc. It is crucial to secure the communication happening between the node and the cloud.

The MAXQ1065 offers enhanced security features for sensor-to-cloud and sensorto-gateway communication:

• Enables the implementation of transport layer security (TLS) protocol, ensuring secure and encrypted data transmission. TLS verifies authenticity and safeguards sensitive information, making it essential for secure communication between nodes and the cloud.

• Facilitates secure communication for proprietary sensor-to-gateway or nodeto-gateway connections. The controller helps establish a protected communication channel by enabling key exchange and data encryption, enhancing security for RF-based or other proprietary protocols.

• Offers additional security features like node authentication, trusted node operation, secure boot, and secure firmware updates.

Table 1: Overview of Components of Industrial Robots/Cobots

These features enhance system security by validating node identity, ensuring trusted operations, and protecting against unauthorized modifications.

• Secure life cycle management and key management ensure that assets remain secure throughout the device/product’s life cycle.

Sensor Data Protection

• Data at rest can be encrypted with ChipDNA technology.

• Critical calibration data of sensor or sensor configuration information can be stored within the secure storage of the MAXQ1065 to prevent it from tampering or leaking. Further, it can be stored encrypted in the system.

See Figure 4.

• ADI’s authenticators enable secure feature enablement, protecting valuable intellectual property.

Secure PLC to Node Communication

It helps enable TLS protocol, which is a widely used transport layer security protocol in internet protocol-based communications.

Joint Authentication in Robots

Implementing joint authentication (see Figure 7) in robots significantly enhances overall security by ensuring that only legitimate and authorized entities can interact within the robotic system. It effectively prevents unauthorized access, strengthens communication security, and contributes to the system’s overall integrity and reliability.

Joint Secure Boot

Joint secure boot (see Figure 8) in robots provides a strong foundation for a secure and trusted operating environment. It protects against unauthorized software execution, malware, and tampering, enhancing system security and reliability. By establishing a chain of trust and verifying the integrity of software components, joint secure boot ensures the overall integrity and authenticity of the robotic system’s operation. Joint secure updates are also enabled in a similar way.

Selective Feature Enablement in Joint and Robot Controller

Post successful secure boot the application microcontroller unit (MCU)/processor/ field programmable gate array (FPGA) can read the secure configurable memory of the authenticator/coprocessor to selectively enable the feature in the joint/robot controller. See Figure 9. Integration for the MAXQ1065 to enable the direct node to cloud security.

Supply Chain Security

Supply chain security includes broad topics

See Figure 5.

• Prevention of product clones (counterfeit).

• Securing software-based feature enablement to prevent IP loss and revenue loss.

• Verification of hardware authenticity. See Figure 6.

Supply chain security can be easily enabled by using ADI’s secure authenticators.

• Preprogrammed authenticators from ADI provide robust protection against counterfeiting.

Secure authenticators can help secure communication, for example, between PLCs and actuators or sensors and between PLCs and the supervisory control and data acquisition (SCADA) control system (in the PLC, not in the SCADA system).

Figure

Figure 6

Sensor data protection.

© ADI

Figure 4

BUILDING SECURE ROBOTIC CONTROL SYSTEMS

Calibration Data Storage − Joint and Robot Controller

Calibration data storage is critical to maintaining accurate measurements in peripherals that undergo individual calibration at the factory. By securely storing this data within an authenticator, organizations can ensure its integrity and protect it from unauthorized access.

The host system can then retrieve and utilize this stored data, enabling more precise and reliable measurements from the peripherals. Secure calibration data storage enhances the overall accuracy and performance of the system, providing valuable insights and maintaining high quality standards.

Joint Secure Communication

Joint secure communication enhances the overall security posture of a robotic system, ensuring trusted and protected data exchange. See Figure 10.

CONCLUSION

In securing the future of robotics, cybersecurity is paramount. Robust measures, such as secure authentication, encrypted communication, and supply chain security, are crucial to protect against threats.

ADI’s products and solutions provide advanced security features, ensuring the integrity and reliability of robotic systems. By prioritizing cybersecurity and leveraging ADI’s expertise, we can unlock the full potential of robotics while safeguarding against emerging risks in an interconnected world.

About the Author

Manoj Rajashekaraiah is a principal engineer specializing in software systems design within the Security Business Unit at Analog Devices. With a strong focus on embedded device security, he excels in creating safety, security, and sensor software for automotive and IoT applications. Manoj is a seasoned presenter and blogger with a passion for sharing knowledge, having shared his insights at conferences like IEEE INIS and VDA Automotive SYS. He is a published author on embedded.com and regularly delivers talks at institutes in Karnataka.

Manoj holds a master’s degree in embedded systems from BITS Pilani, India.

References

1) Jean-Paul A. Yaacoub, Hassan N. Noura, Ola Salman, and Ali Chehab.

“Robotics Cyber Security: Vulnerabilities, Attacks, Countermeasures, and Recommendations.”

International Journal of Information Security, March 2021.

2) Christophe Tremlet.

“The IEC 62443 Series of Standards: How to Defend Against Infrastructure Cyberattacks.”

Analog Devices, Inc., April 2023.

3) “ Protect Your R&D Investment with Secure Authentication.” Analog Devices, Inc.

4) “The Basics of Using the DS28S60.” Analog Devices, Inc.

■ Analog Devices www.analog.com

Joint authentication.

Figure 7

A typical joint block diagram.

Figure 9

Joint secure boot.

Figure 8 Joint secure communication.

Flexible and precise: Ultrasonic sensors with adjustable sound cone

Ultrasonic sensors are used in many industries. They detect objects almost irrespective of their material characteristics. Ultrasonic sensors have proven effective even with glossy, reflective, extremely dark or transparent surfaces as well as with liquids and solve challenges where optical sensors reach their limits.

The new 420B series includes switching and measuring ultrasonic sensors in compact cubic plastic housings. With the HTU 420B ultrasonic sensors in the standard segment featuring one switching output (push-pull), we offer an economical solution in black plastic housings.

The HTU 420B ultrasonic sensors in red housings with their IO-Link interface and two switching outputs are suitable for demanding detection tasks. The adjustable sound cone enables extremely flexible use of the sensors and minimizes the number of different variants required in the system: One sensor type can be used for different applications. With a narrow sound cone, it is possible to detect fill levels through

New cubic ultrasonic sensors with small dead zone and three adjustable sound cone widths for precise switching and measurement results

small openings, for example. A wide sound cone is suitable for e.g. reliably detecting diffusely reflective objects such as products with an uneven or complex surface or structure. An interruption filter detects brief changes in measurement within a certain interval caused by interfering objects (e.g. agitators) and can suppress interfering signals. Two independent switching outputs enable two positions to be monitored or two fill levels to be detected.

The DMU 420B ultrasonic distance sensors with analog output (either current or voltage) also have an IO-Link interface and adjustable sound cone. Here, the signal level of the current or voltage signal is proportionate to the object distance. The new sensors of the 420B series replace the models of the 420 series. They have an equivalent or higher operating range and smaller dead zones than the predecessor series. The new sensors of the 420B series are available in three operating ranges: 10 – 250 mm; 15 – 500 mm și 20 – 1000 mm.

The cylindrical ultrasonic sensors of the 412B series are also new. They are also equipped with an adjustable sound cone and an IO-Link interface and extend the existing range of M12 housings.

Advantages for you

■ Detection nearly independent of object and surface

■ Compact ultrasonic sensors and distance sensors in one series

■ Maximum flexibility for any application thanks to adjustable sound cone (narrow, medium, wide)

■ Monitoring of two positions or fill levels by means of two switching outputs

■ Interfering objects can be suppressed via the IO-Link interface (interruption filter)

■ High operating ranges (three ranges) and small dead zones

■ Installation in constrained spaces thanks to small design

■ Easy parameterization via teach button, IO-Link interface or teach input

Flexible use thanks to adjustable sound cone

The ultrasonic sensors with IO-Link interface have an adjustable sound cone. The width of the sound cone can be adapted to the respective application. This ensures universal and flexible use of the sensors as well as optimum switching and measurement results. Via the IO-Link interface, the sound cone can be set to three ranges: narrow, medium or wide. Narrow sound cones are suitable for e.g. fill level detection through small container openings, a wide sound cone is generally used for detection or measurement tasks in larger ranges (e.g. with bulk material) or in the case of objects with complex geometries or surfaces.

Small and compact design

Cubic sensors are often used for applications with limited installation space. With their compact dimensions (20.5 x 41.0 x 15.0 mm), the new measuring and switching ultrasonic sensors are specially developed for applications where space is constrained.

Applications

Filling level monitoring with differently sized container openings

Requirement:

After the filling process, the fill level must be checked in order to avoid underfilling or overfilling. It must be possible to use the sensor system for both small and large container openings.

Solution:

The HTU 420B ultrasonic sensors have an adjustable sound cone. Depending on the application, a narrow, medium or wide sound cone can be selected. This enables flexible use of the sensors and reduces the number of different variants in the system.

Monitoring of roll diameter

Requirement:

The diameter of rolled goods must be monitored continuously in order to safeguard the availability of the rolled material and to ensure that rolls are changed in a timely manner. Transparent, glossy, colorful, black or metalized materials must also be reliably detected by the sensor.

Solution:

The ultrasonic distance sensors of the DMU 420B series supply a continuous analog output signal (either current or voltage) to the machine control. This enables the roll to be changed in good time.